R: The 'linkcomm' package

linkcomm-package {linkcomm} | R Documentation

## The `linkcomm` package

### Description

`linkcomm` provides tools for the generation, visualization, and analysis of link communities in networks of arbitrary size and type.

### Details

Link communities reveal the nested and overlapping structure in networks, and uncover the key nodes that form connections to multiple communities. `linkcomm` provides tools for generating, visualizing, and analysing link communities in networks of arbitrary size and type.

For a more detailed overview of how to use the package:
`vignette(topic = "linkcomm", package = "linkcomm")`
To run an interactive demonstration of `linkcomm` within R:
`demo(topic = "linkcomm", package = "linkcomm")`

### Author(s)

Alex T. Kalinka alex.t.kalinka@gmail.com

### References

Ahn, Y.Y., Bagrow, J.P., and Lehmann, S. (2010). Link communities reveal multiscale complexity in networks. Nature 466, 761-764.

Becker, E., Robisson, B., Chapple, C.E., Guenoche, A. and Brun, C. (2012) Multifunctional proteins revealed by overlapping clustering in protein interaction network. Bioinformatics 28, 84-90.

Kalinka, A.T. and Tomancak, P. (2011). linkcomm: an R package for the generation, visualization, and analysis of link communities in networks of arbitrary size and type. Bioinformatics 27, 2011-2012.

Spencer, R. (2010). http://scaledinnovation.com/analytics/communities/comlinks.html

### See Also

`getLinkCommunities`, `getOCG.clusters`, `plot.linkcomm`, `pp_rnapol`, `lesmiserables`, `karate`, `weighted`, `igraph`, `RColorBrewer`, `grid`

### Examples

    ## Generate graph and extract link communities.
    g <- swiss[,3:4]
    lc <- getLinkCommunities(g)

    ## Plot a graph layout of the link communities.
    plot(lc, type = "graph")

    ## Use a Spencer circle layout.
    plot(lc, type = "graph", layout = "spencer.circle")

    ## Calculate a community-based measure of node centrality.
    getCommunityCentrality(lc)

    ## Find nested communities.
    getAllNestedComm(lc)

    ## Uncover the relatedness between communities.
    getClusterRelatedness(lc)

[Package linkcomm version 1.0-14 Index]